Synchronization Research And Application Of Coupled Chay Neuron System

With high nonlinearity,neuron system is an extremely complex neural network system composed of many neuronal cells that are connected to each other.Therefore,many processes of neuron,such as power generation & discharge mode,information transmission and coding show abundant dynamic phenomena.In general,information transmission between neurons is realized in the form of power discharge and generation,coupling and synchronization of neurons,that is,the coupled neuron system transmits information synchronously.Hence,it is of important value to study the change of power generation & discharge rhythm,as well as the mutual transition of rhythm of the coupled neuron system under parameter matching or external stimulation.In this thesis,the power generation & discharge mode and synchronization of Chay neuron model and coupled Chay neuron system are studied by C language,MATLAB numerical simulation and relevant theoretical demonstration.Firstly,the background and significance of this subject study,the development status of neurons at home and abroad,some knowledge related to neurons,the related technology,theoretical knowledge and several classical neuron mathematical models involved in this research are introduced.Secondly,studying on nonlinear dynamic behavior of Chay neurons under single-parameter matching.The phenomena of adding period,double period and chaos of Chay neuron model can be observed intuitively in ISI bifurcation diagram under single-parameter control,and the corresponding phenomenon of power generation & discharge can also be observed in the corresponding time response diagram and phase diagram.Thirdly,the synchronization behavior of coupled Chay neuron system is studied.In this thesis,the change of power generation & discharge rhythm and synchronization of Chay neuron system under electrosynaptic coupling and chemical synaptic coupling are studied respectively,and the effects on neuron system by adding external stimuli(time delay and noise)are discussed and analyzed respectively.The results show that the discrete coupling strength,time delay and noise can influence the synchronization behavior of coupled neuron system to some extent,which not only provides certain theoretical basis for eliminating pathological synchronization or asynchronism in the medical field,but also helps to further study the complex dynamic behavior and mechanism of biological neural network system in the future.Then,the sensitivity of the coupled neuron system to the initial value and the high randomness of its analytical solution are applied to the embedding of image watermarking,which makes the watermarking image more robust and the extracted watermarking have better anti-jamming,so that the original image products can be more effectively protected.Finally,the work done in this thesis is summarized and the future research directions are prospected.